Fruit Disease's Identification and Classification Using Deep Learning Model

Now days Fruits is being produced from alot of countries as the global fruit production reached up to 2914.27 production in thousand metric tons and in the upcoming years a lot of countries want to increase the production. However, some challenges and problems persist to exist through the fruits production like the quality of the fruit, the cost of the production, the quality of the seed and the illness of the fruit itself. There are types of recognized Diseases in the apples such as blotch, scab, and rotten diseases, and for the citrus, Black spot, Scab Citrus, and Citrus Canker. In this project, Our aim is to identify the best transfer learning model that is able to achieve the most extraordinary accuracy through the early detection of fruit diseases. Five different types of transfer learning models are presented, and they are being used in this proposed solution as the customized CNN model achieved the highest accuracy that reached up to 99.16%.